Quantification choices for individual differences: An example of mapping self-report to psychophysiological responses.

Individual differences Intolerance of uncertainty Meta-analysis Multiverse-type analysis Psychophysiology Threat extinction Trait anxiety

Journal

International journal of psychophysiology : official journal of the International Organization of Psychophysiology
ISSN: 1872-7697
Titre abrégé: Int J Psychophysiol
Pays: Netherlands
ID NLM: 8406214

Informations de publication

Date de publication:
30 Aug 2024
Historique:
received: 05 04 2024
revised: 01 08 2024
accepted: 27 08 2024
medline: 2 9 2024
pubmed: 2 9 2024
entrez: 1 9 2024
Statut: aheadofprint

Résumé

A popular focus in affective neuroscience research has been to map the relationships between individual differences (e.g. personality and environmental experiences) and psychophysiological responses, in order to further understand the effect of individual differences upon neurobehavioral systems that support affect and arousal. Despite this trend, there have been a lack of practical examples demonstrating how the quantification of individual differences (e.g. categorical or continuous) impacts the observed relationships between different units of analysis (e.g. self-report > psychophysiological responses). To address this gap, we conducted a two-stage aggregated meta-analysis of self-reported intolerance of uncertainty (IU) and skin conductance responses during threat extinction (k = 18, n = 1006) using different quantification choices for individual differences in self-reported intolerance of uncertainty (continuous, categorical via median split, and categorical via extremes - one standard deviation above/below). Results from the meta-analyses revealed that the different quantification techniques produced some consistent (e.g. higher IU was significantly associated with skin conductance responding during late extinction training) and inconsistent IU-related effects. Furthermore, the number of statistically significant effects and effect sizes varied based on the quantification of individual differences in IU (e.g. categorical, compared to continuous was associated with more statistically significant effects, and larger effect sizes). The current study highlights how conducting different quantification methods for individual differences may help researchers understand the individual difference construct of interest (e.g. characterisation, measurement), as well as examine the stability and reliability of individual difference-based effects and correspondence between various units of analysis.

Identifiants

pubmed: 39218250
pii: S0167-8760(24)00131-4
doi: 10.1016/j.ijpsycho.2024.112427
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

112427

Informations de copyright

Copyright © 2024. Published by Elsevier B.V.

Auteurs

Jayne Morriss (J)

School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, UK. Electronic address: j.morriss@soton.ac.uk.

Nicolo Biagi (N)

Henley Business School, Business Informatics Systems and Accounting, Informatics Research Centre, University of Reading, UK.

Shannon Wake (S)

School of Psychology, University of Reading, UK.

Classifications MeSH